Code
if(base::interactive()) {
params <- rmarkdown::yaml_front_matter(here::here("analysis/03_beta_diversity.qmd"))$params
}
factor_of_interest <- params$factor_of_interestWhere we analyse the effect of a factor on local diversity
Date: October 29, 2024
See the documentation of the MiscMetabar package for example of alpha diversity analysis.
if(base::interactive()) {
params <- rmarkdown::yaml_front_matter(here::here("analysis/03_beta_diversity.qmd"))$params
}
factor_of_interest <- params$factor_of_interestlibrary(knitr)
library(targets)
library(MiscMetabar)
here::i_am("analysis/02_alpha_diversity.qmd")
source(here::here("R/styles.R"))d_pq <- clean_pq(tar_read("d_vs", store=here::here("_targets/")))Cleaning suppress 2 taxa and 1 samples.
hill_pq(subset_samples(d_pq, Type %in% c("Mix", "Mono")), factor_of_interest, one_plot = TRUE) &
(
theme_idest(
subtitle_size = 8,
plot_title_size = 12,
plot_margin = margin(5, 10, 5, 10),
axis_title_size = 9,
axis_text_size = 8
) + theme(legend.position = "none")
) Taxa are now in rows.
3 out of 3 Hill scales do not show any global trends with you factor Type. Tuckey HSD plot is not informative for those Hill scales. Letters are not printed for those Hill scales
MiscMetabar::accu_plot_balanced_modality(d_pq, factor_of_interest, nperm=20) + theme_idest()`set.seed(1)` was used to initialize repeatable random subsampling.
Please record this for your records so others can reproduce.
Try `set.seed(1); .Random.seed` for the full vector
...
Warning in rarefy_sample_count_by_modality(rarefy_even_depth(physeq, rngseed = 1, : The number of final levels (sam_data of the output phyloseq
object) is not equal to the inital (sam_data of the input
phyloseq object) number of levels in the factor: 'Type'
Warning in max(dff$xlab, na.rm = TRUE): aucun argument pour max ; -Inf est
renvoyé
|
| | 0%
|
|== | 5%
|
|===== | 10%
Error in plist[, , i] <- as.matrix(suppressWarnings(suppressMessages(accu_plot(rarefy_sample_count_by_modality(rarefy_even_depth(physeq, : le nombre d'objets à remplacer n'est pas multiple de la taille du remplacement
ggbetween_pq(d_pq, factor_of_interest)$plot_Hill_0
$plot_Hill_1
$plot_Hill_2
Session information are detailed below. More information about the machine, the system, as well as python and R packages, are available in the file data_final/information_run.txt .
sessionInfo()R version 4.4.1 (2024-06-14)
Platform: x86_64-pc-linux-gnu
Running under: Debian GNU/Linux 12 (bookworm)
Matrix products: default
BLAS: /usr/lib/x86_64-linux-gnu/blas/libblas.so.3.11.0
LAPACK: /usr/lib/x86_64-linux-gnu/lapack/liblapack.so.3.11.0
locale:
[1] LC_CTYPE=fr_FR.UTF-8 LC_NUMERIC=C
[3] LC_TIME=fr_FR.UTF-8 LC_COLLATE=fr_FR.UTF-8
[5] LC_MONETARY=fr_FR.UTF-8 LC_MESSAGES=fr_FR.UTF-8
[7] LC_PAPER=fr_FR.UTF-8 LC_NAME=C
[9] LC_ADDRESS=C LC_TELEPHONE=C
[11] LC_MEASUREMENT=fr_FR.UTF-8 LC_IDENTIFICATION=C
time zone: Europe/Paris
tzcode source: system (glibc)
attached base packages:
[1] stats graphics grDevices datasets utils methods base
other attached packages:
[1] MiscMetabar_0.10.1 purrr_1.0.2 dplyr_1.1.4 dada2_1.32.0
[5] Rcpp_1.0.13 ggplot2_3.5.1 phyloseq_1.48.0 targets_1.8.0
[9] knitr_1.48
loaded via a namespace (and not attached):
[1] RColorBrewer_1.1-3 jsonlite_1.8.9
[3] datawizard_0.13.0 correlation_0.8.5
[5] magrittr_2.0.3 SuppDists_1.1-9.8
[7] farver_2.1.2 rmarkdown_2.28
[9] zlibbioc_1.50.0 vctrs_0.6.5
[11] multtest_2.60.0 memoise_2.0.1
[13] Rsamtools_2.20.0 paletteer_1.6.0
[15] effectsize_0.8.9 htmltools_0.5.8.1
[17] S4Arrays_1.4.1 BWStest_0.2.3
[19] Rhdf5lib_1.26.0 SparseArray_1.4.8
[21] rhdf5_2.48.0 htmlwidgets_1.6.4
[23] plyr_1.8.9 cachem_1.1.0
[25] GenomicAlignments_1.40.0 igraph_2.1.1
[27] lifecycle_1.0.4 iterators_1.0.14
[29] pkgconfig_2.0.3 Matrix_1.7-0
[31] R6_2.5.1 fastmap_1.2.0
[33] PMCMRplus_1.9.12 GenomeInfoDbData_1.2.12
[35] MatrixGenerics_1.16.0 BayesFactor_0.9.12-4.7
[37] digest_0.6.37 colorspace_2.1-1
[39] ShortRead_1.62.0 rematch2_2.1.2
[41] patchwork_1.3.0 S4Vectors_0.42.1
[43] ps_1.8.0 rprojroot_2.0.4
[45] prismatic_1.1.2 GenomicRanges_1.56.2
[47] base64url_1.4 hwriter_1.3.2.1
[49] vegan_2.6-8 labeling_0.4.3
[51] fansi_1.0.6 httr_1.4.7
[53] abind_1.4-8 mgcv_1.9-1
[55] compiler_4.4.1 here_1.0.1
[57] withr_3.0.1 backports_1.5.0
[59] BiocParallel_1.38.0 performance_0.12.4
[61] ggsignif_0.6.4 MASS_7.3-61
[63] DelayedArray_0.30.1 biomformat_1.32.0
[65] permute_0.9-7 tools_4.4.1
[67] ape_5.8 statsExpressions_1.6.0
[69] glue_1.8.0 callr_3.7.6
[71] nlme_3.1-165 rhdf5filters_1.16.0
[73] grid_4.4.1 cluster_2.1.6
[75] reshape2_1.4.4 ade4_1.7-22
[77] generics_0.1.3 gtable_0.3.5
[79] tidyr_1.3.1 data.table_1.16.2
[81] utf8_1.2.4 XVector_0.44.0
[83] BiocGenerics_0.50.0 ggrepel_0.9.6
[85] foreach_1.5.2 pillar_1.9.0
[87] stringr_1.5.1 splines_4.4.1
[89] lattice_0.22-6 gmp_0.7-5
[91] renv_1.0.11 survival_3.7-0
[93] deldir_2.0-4 ggstatsplot_0.12.4
[95] tidyselect_1.2.1 pbapply_1.7-2
[97] Biostrings_2.72.1 IRanges_2.38.1
[99] SummarizedExperiment_1.34.0 stats4_4.4.1
[101] xfun_0.48 Biobase_2.64.0
[103] matrixStats_1.4.1 stringi_1.8.4
[105] UCSC.utils_1.0.0 yaml_2.3.10
[107] kSamples_1.2-10 evaluate_1.0.1
[109] codetools_0.2-20 interp_1.1-6
[111] tibble_3.2.1 BiocManager_1.30.25
[113] multcompView_0.1-10 cli_3.6.3
[115] RcppParallel_5.1.9 secretbase_1.0.3
[117] parameters_0.23.0 munsell_0.5.1
[119] processx_3.8.4 GenomeInfoDb_1.40.1
[121] zeallot_0.1.0 coda_0.19-4.1
[123] png_0.1-8 parallel_4.4.1
[125] MatrixModels_0.5-3 bayestestR_0.15.0
[127] latticeExtra_0.6-30 jpeg_0.1-10
[129] bitops_1.0-9 Rmpfr_0.9-5
[131] pwalign_1.0.0 mvtnorm_1.3-1
[133] scales_1.3.0 insight_0.20.5
[135] crayon_1.5.3 rlang_1.1.4
@online{taudière2024,
author = {Taudière, Adrien},
title = {Alpha-Diversity},
date = {2024-10-29},
langid = {en}
}